The graphics processing unit (GPU) did not begin as a pillar of supercomputing or the engine behind artificial‑intelligence chatbots.

This article examines five key hardware strategies for building energy-efficient AI acceleration: dedicated accelerator ...

China unveils Darwin Monkey, the world's first brain-like supercomputer with over 2 billion neurons, marking a major leap in ...

Generative AI is arguably the most complex application that humankind has ever created, and the math behind it is incredibly ...

GPT-5 is more than an upgrade. It aims to be a single, smarter system that blends reasoning, multimodality, cost efficiency, ...

Google released its first publicly available "multi-agent" AI system, which uses more computational resources, but produces ...

Storage.AI focuses on data-handling efficiency after packets reach their destinations. Founding members include AMD, Cisco, ...

Researchers at The University of Manchester's National Graphene Institute have developed a new class of programmable ...

Raja Koduri, the influential GPU architect known for his work at ATI Technologies, AMD, Apple, and Intel, has introduced a ...

The meteoric rise of NVIDIA’s GPU technology in accelerating AI has captivated the world and, in the process, given rise to ...

Within the next two years, 80% of AI compute is projected to be devoted to inference and just 20% to training.

The humble database offers the key to giving AI context and adaptation, accessing data beyond its training cutoff.